A parallel-processing hydrocarbon (HC) migration and accumulation methodology is applied to basin data to determine migration pathways and traps for high-resolution petroleum system modeling. HC is determined in parallel to have been expelled in source rocks associated with a plurality of grid cells divided into one or more subdomains. Potential trap peaks are identified within the plurality of grid cells. An invasion percolation (IP) process is performed until the HC stops migrating upon arrival to the plurality of trap peaks. A determination is made as to whether the grid cells containing HC contains an excess volume of HC. An accumulation process is performed to model the filling of the HC at a trap associated with the identified potential trap peaks. The trap boundary cell list is updated in parallel together with an HC potential value. Trap filling terminates when excess HC is depleted or a spill point is reached.

A parallel-processing hydrocarbon (HC) migration and accumulation methodology is applied to basin data to determine migration pathways and traps for high-resolution petroleum system modeling. HC is determined in parallel to have been expelled in source rocks associated with a plurality of grid cells divided into one or more subdomains. Potential trap peaks are identified within the plurality of grid cells. An invasion percolation (IP) process is performed until the HC stops migrating upon arrival to the plurality of trap peaks. A determination is made as to whether the grid cells containing HC contains an excess volume of HC. An accumulation process is performed to model the filling of the HC at a trap associated with the identified potential trap peaks. The trap boundary cell list is updated in parallel together with an HC potential value. Trap filling terminates when excess HC is depleted or a spill point is reached.

A parallel-processing hydrocarbon (HC) migration and accumulation methodology is applied to basin data to determine migration pathways and traps for high-resolution petroleum system modeling. HC is determined in parallel to have been expelled in source rocks associated with a plurality of grid cells divided into one or more subdomains. Potential trap peaks are identified within the plurality of grid cells. An invasion percolation (IP) process is performed until the HC stops migrating upon arrival to the plurality of trap peaks. A determination is made as to whether the grid cells containing HC contains an excess volume of HC. An accumulation process is performed to model the filling of the HC at a trap associated with the identified potential trap peaks. The trap boundary cell list is updated in parallel together with an HC potential value. Trap filling terminates when excess HC is depleted or a spill point is reached.

A parallel-processing hydrocarbon (HC) migration and accumulation methodology is applied to basin data to determine migration pathways and traps for high-resolution petroleum system modeling. HC is determined in parallel to have been expelled in source rocks associated with a plurality of grid cells divided into one or more subdomains. Potential trap peaks are identified within the plurality of grid cells. An invasion percolation (IP) process is performed until the HC stops migrating upon arrival to the plurality of trap peaks. A determination is made as to whether the grid cells containing HC contains an excess volume of HC. An accumulation process is performed to model the filling of the HC at a trap associated with the identified potential trap peaks. The trap boundary cell list is updated in parallel together with an HC potential value. Trap filling terminates when excess HC is depleted or a spill point is reached.

A system, method, or apparatus for generating a blast plan that can receive blast data comprising geological properties of a blast site, blasthole parameters, and available explosive product. A pattern footage can be determined based on a relationship between the face height, the specific energy of the available explosive product, and the geological properties of the bench. The burden and spacing can be determined from the pattern footage.

A device may receive a floating-point function. The floating-point function may be a function described in a programming language that uses floating-point representation. The device may determine that fixed-point program code, associated with the floating-point function, is to be generated. The device may determine that the floating-point function is to be replaced with a replacement construct before the fixed-point program code is generated. The replacement construct may be described in the programming language and may be capable of conversion from the floating-point representation to a fixed-point representation. The device may determine parameters associated with generating the replacement construct. The parameters may be determined based on an evaluation of the floating-point function. The device may generate the replacement construct based on the parameters. The device may replace the floating-point function with the replacement construct. The device may generate the fixed-point program code based on the replacement construct.

A parallel-processing hydrocarbon (HC) migration and accumulation methodology is applied to basin data to determine migration pathways and traps for high-resolution petroleum system modeling. HC is determined in parallel to have been expelled in source rocks associated with a plurality of grid cells divided into one or more subdomains. Potential trap peaks are identified within the plurality of grid cells. An invasion percolation (IP) process is performed until the HC stops migrating upon arrival to the plurality of trap peaks. A determination is made as to whether the grid cells containing HC contains an excess volume of HC. An accumulation process is performed to model the filling of the HC at a trap associated with the identified potential trap peaks. The trap boundary cell list is updated in parallel together with an HC potential value. Trap filling terminates when excess HC is depleted or a spill point is reached.

A device is provided for computing a function value of a function F. The device includes a memory, a truncator unit, a selector unit, and an evaluator unit. The memory contains a look-up table comprising a set of entries, each entry having associated with it a domain and an approximation function for approximating F on the associated domain. The truncator unit is arranged to truncate or round a first value X1 to generate a second value X2. The selector unit is arranged to select an entry of the lookup-table according to the second value X2, thus selecting the approximation function that is associated with the selected entry. The evaluator unit is arranged to determine the function value of the selected approximation function at the first value X1.

A datapath circuit may include a digital multiply and accumulate circuit (MAC) and a digital hardware calculator for parallel computation. The digital hardware calculator and the MAC may be coupled to an input memory element for receipt of input operands. The MAC may include a digital multiplier structure with partial product generators coupled to an adder to multiply a first and second input operands and generate a multiplication result. The digital hardware calculator may include a first look-up table coupled between a calculator input and a calculator output register. The first look-up table may include table entry values mapped to corresponding math function results in accordance with a first predetermined mathematical function. The digital hardware calculator may be configured to calculate, based on the first look-up table, a computationally hard mathematical function such as a logarithm function, an exponential function, a division function and a square root function.

Mathematical functions are computed in a single pipeline performing a polynomial approximation (e.g. a quadratic approximation, or the like) using data tables for RCP, SQRT, EXP or LOG using a single pipeline according and opcodes. SIN and COS are also computed using the pipeline according to the approximation ((1)^IntX)*Sin(*Min(FracX, 1.0FracX)/Min(FracX, 1.0FracX). A pipeline portion approximates Sin(*FracX) using tables and interpolation and a subsequent stage multiplies this approximation by FracX. For input arguments of x close 1.0. LOG 2(x1)/(x1) is computed using a first pipeline portion using tables and interpolation and subsequently multiplied by (x1). A DIV operation may also be performed with input arguments scaled up to avoid underflow as needed. Inverse trigonometric functions may be calculated using a pre-processing stage and post processing stage in order to obtain multiple inverse trigonometric functions from a single pipeline.